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Integrative bioinformatical analysis of clear cell renal cell carcinoma (1138.10)
Author(s) -
Butz Henriett,
Nofech Mozes Roy,
Rotondo Fabio,
Kovacs Kalman,
Patocs Attila,
Szabo Peter,
Yousef George
Publication year - 2014
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.28.1_supplement.1138.10
Subject(s) - clear cell renal cell carcinoma , biology , carcinogenesis , aryl hydrocarbon receptor , microrna , cancer research , transcriptome , renal cell carcinoma , computational biology , bioinformatics , metabolomics , cell , medicine , oncology , transcription factor , gene , genetics , gene expression
Background. Clear cell renal cell carcinoma (ccRCC) is the most common adult neoplasm of the kidney. Better understanding of the molecular pathogenesis may lead to new therapeutic options. Aim. Our aim was to assemble transcriptomic, proteomic and miRNA data using an integrative approach. Methods. Available mRNA, miRNA and protein data were collected from 593 ccRCC and 389 normal kidneys. We performed pathway analysis. TCGA database and immunohistochenmitry were used for validation. Functional analyses were undertaken on cell line model. Results. Metabolic processes were the most significant signalling pathways, and we validated Aryl‐Hydrocarbon Receptor (AHR) signalling to be involved in tumorigenesis. Using network analysis, we identified GRHL2 as diagnostic marker and drug target. KIAA0101 was found to enhance tumor cell migration and invasion. We also demonstrated that KIAA0101 overexpression correlates with poor prognosis and may represent a diagnostic marker. We identified miR‐139‐5p as the miRNA mostly affecting the network targeting ZEB1, TCF4, ETS1 and CCND2. Conclusions. Using integrative bioinformatical analyses we identified the most characteristic pathways and molecules. Some of them may be applicable as biomarkers or new, potential drug targets.